Jo Hardin, Pomona College
8.5.2020
With our deepest respects to the Tongva and Serrano Peoples, past, present, and emerging.
Just under 100 datasets. https://openpolicing.stanford.edu/data/
raleigh_df %>%
# remove missing data
filter(!is.na(sex) & !is.na(race)) %>%
# use group_by and summarize to count number of stops per category
group_by(sex, race) %>%
summarize(count = n()) %>%
ungroup() %>%
# find the percentage of age/race stops
mutate(percentage = round(prop.table(count), digits = 2)) %>%… continued
# plot percentages
ggplot(mapping = aes(x = sex, y = percentage,
fill = race,
label = scales::percent(percentage))) +
geom_bar(position = "dodge", stat = "identity") +
# adjust labels
geom_text(position = position_dodge(width = .9),
vjust = -0.5,
size = 3) +
scale_y_continuous(labels = scales::percent) +
# provide labels
ggtitle("Race & gender breakdown, % out of total")Accessing, joining, and wrangling all the datasets.
With facet_geo
searchn.b., all the observations were traffic stops, so we can’t model demographics of who was pulled over (model search instead).
raleigh_search <- glm(formula = search ~ age * race,
family = "binomial", data = raleigh_df,
subset = (race %in% c("black", "white")))
raleigh_search %>% tidy()## # A tibble: 4 x 5
## term estimate std.error statistic p.value
## <chr> <dbl> <dbl> <dbl> <dbl>
## 1 (Intercept) -1.90 0.0240 -78.9 0.
## 2 age -0.0327 0.000759 -43.1 0.
## 3 racewhite -0.785 0.0402 -19.5 5.39e-85
## 4 age:racewhite 0.00200 0.00125 1.60 1.10e- 1
Data Feminism https://datafeminism.io/
Image credit: Interaction Institute for Social Change | Artist: Angus Maguire.
What are the systems that have created structural racial discrepancies in the US?
Pierson at al. “A large-scale analysis of racial disparities in police stops across the United States” (Nature Human Behaviour, 2020)
Our results indicate that police stops and search decisions suffer from persistent racial bias and point to the value of policy interventions to mitigate these disparities.
While the research shows that stops are neither equal nor equitable, a discussion on equity belongs in the conversation around racial discrepancies in traffic stops.
The undergraduates who did the complete analysis and wrote the report are Pomona College students: Amber Lee (‘22), Arm Wonghirundacha (‘22), Emma Godfrey (‘21), Ethan Ong (‘21), Ivy Yuan (‘21), Oliver Chang (‘22), and Will Gray (‘22).